| import gradio as gr
|
| import requests
|
|
|
|
|
| BASE_URL = "http://localhost:1234/api/v0"
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|
|
|
|
| def chat_with_lmstudio(messages, model, temperature=0.7, max_tokens=150):
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| endpoint = f"{BASE_URL}/chat/completions"
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| payload = {
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| "model": model,
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| "messages": messages,
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| "temperature": temperature,
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| "max_tokens": max_tokens,
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| "stream": False
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| }
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| try:
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| response = requests.post(endpoint, json=payload)
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| response.raise_for_status()
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| data = response.json()
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| return data["choices"][0]["message"]["content"]
|
| except requests.RequestException as e:
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| return f"Error: {str(e)}"
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|
|
|
|
| def text_completion(prompt, model, temperature=0.7, max_tokens=150):
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| endpoint = f"{BASE_URL}/completions"
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| payload = {
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| "model": model,
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| "prompt": prompt,
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| "temperature": temperature,
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| "max_tokens": max_tokens,
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| "stream": False
|
| }
|
| try:
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| response = requests.post(endpoint, json=payload)
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| response.raise_for_status()
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| data = response.json()
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| return data["choices"][0]["text"]
|
| except requests.RequestException as e:
|
| return f"Error: {str(e)}"
|
|
|
|
|
| def text_embedding(text, model):
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| endpoint = f"{BASE_URL}/embeddings"
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| payload = {
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| "model": model,
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| "input": text
|
| }
|
| try:
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| response = requests.post(endpoint, json=payload)
|
| response.raise_for_status()
|
| data = response.json()
|
| return data["data"][0]["embedding"]
|
| except requests.RequestException as e:
|
| return f"Error: {str(e)}"
|
|
|
|
|
| def chat_interface(user_message, history, model="granite-3.0-2b-instruct"):
|
| if history is None:
|
| history = []
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| history.append({"role": "user", "content": user_message})
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| assistant_response = chat_with_lmstudio(history, model=model)
|
| history.append({"role": "assistant", "content": assistant_response})
|
| conversation = [(h["content"], history[i+1]["content"]) for i, h in enumerate(history[:-1]) if h["role"] == "user"]
|
| return conversation, history
|
|
|
| with gr.Blocks() as demo:
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| gr.Markdown("# LM Studio API Interface")
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|
|
| with gr.Tab("Chat with Model"):
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| chat_history = gr.State([])
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| chat_model = gr.Textbox(value="granite-3.0-2b-instruct", label="Model")
|
| chatbot = gr.Chatbot()
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| msg = gr.Textbox(placeholder="Enter your message", label="User Input")
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| submit_btn = gr.Button("Send")
|
| submit_btn.click(chat_interface, inputs=[msg, chat_history, chat_model], outputs=[chatbot, chat_history])
|
|
|
| with gr.Tab("Text Completion"):
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| completion_prompt = gr.Textbox(placeholder="Enter a prompt for text completion", label="Prompt")
|
| completion_model = gr.Textbox(value="granite-3.0-2b-instruct", label="Model")
|
| completion_output = gr.Textbox(label="Completion")
|
| generate_btn = gr.Button("Generate")
|
| generate_btn.click(text_completion, inputs=[completion_prompt, completion_model], outputs=completion_output)
|
|
|
| with gr.Tab("Text Embeddings"):
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| embedding_text = gr.Textbox(placeholder="Enter text for embeddings", label="Input Text")
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| embedding_model = gr.Textbox(value="text-embedding-nomic-embed-text-v1.5", label="Model")
|
| embedding_output = gr.JSON(label="Embeddings")
|
| embed_btn = gr.Button("Get Embeddings")
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| embed_btn.click(text_embedding, inputs=[embedding_text, embedding_model], outputs=embedding_output)
|
|
|
| demo.launch(share=True)
|
|
|
